PARENT SESSION

7A (2) - Simulation and Modelling
Hall 8
8:30 AM - 10:15 AM, Wednesday, 30 April 2003
Chair: Jischa, M.¹, ¹
Co-chair: Tulbure, I.², ²

(WE8/3) Towards a Globally Applicable Model for Estimating the Dilution of Down-the-Drain Chemicals in Surface Waters.

Whelan, Mick¹, Hodges, Geoff¹, Costello, Jayne¹, ¹ Unilever, Sharnbrook, Bedfordshire, UK

ABSTRACT- Environmental risk assessments for chemicals generally make comparisons between predicted environmental concentrations (PECs) and predicted no effect concentrations (PNECs). For chemicals which are mainly discharged to surface waters via sewers (down-the-drain chemicals), a crude PEC in sewage can be calculated by dividing the mass of substance used per-capita by the domestic per-capita water use. This is then adjusted for removal in sewage treatment (if present) and dilution, after mixing, in the receiving water body. In the absence of local hydrological data, the dilution factor is usually given an arbitrary value (e.g. 10). In this paper, we explore the possibilities for improving predictions of surface water dilution using spatially-referenced global data sets of average monthly runoff and population density. The approach is based on exploiting composite runoff data for the land surface of the earth (on a 0.5 x 0.5 deg lat-lon grid), generated by combining a simple water balance model (based on measured and interpolated precipitation data and estimates of evapotranspiration) with observed river discharge data. This is combined with the UNEP Global Population Distribution Database (1 x 1 deg grid), country-specific domestic water use rates and market data for the chemical of interest (using a Geographical Information System) to give the dilution factor and PEC per grid cell on a mean annual and mean monthly basis. The frequency distribution of runoff, dilution and PECs can also be extracted for a particular country or region. Although the proposed methodology is still very crude, it is superior to the application of arbitrary dilution factors and has great potential as a global-scale screening tool for the risk assessment of chemicals.

Key words: exposure assessment, dilution, global, model